A Cellular Automata Modeling for Visualizing and Predicting Spreading Patterns of Dengue Fever
Abstract: A Cellular Automata
(CA) model is used for visualizing and predicting spreading pattern of the disease.
The main problem of this model is how to find a function that represents an
update rule that changes the state of a cell in time steps affected by
neighborhood. This research aims to develop visualization and prediction model
of the spreading patterns of Dengue Hemorrhagic Fever. The contribution of our
study is to introduce a new approach in defining a probabilistic function that
represents CA transmission rule by employing Von Neumann neighborhood and the
Hidden Markov Model (HMM). This study only considered an infective state which
dedicated particular attention to the spatial distribution of infected areas.
The infected data were devided into four categories and change the definition
of a cell as an area. The evaluation was conducted by comparing the results of
the proposed model to that of one yielded by a Susceptible-Infected-Recovered
(SIR) model. The evaluation result showed that the CA model was capable of
generating patterns that similar to the patterns generated by SIR models with a
similarities value of 0.95.
Author: Puspa Eosina , Taufik
Djatna , Helda Khusun
Journal Code: jptkomputergg160188
